how to forward fill a column values based on the value in another column in same row

Question

I want to forward fill the amount column based on times column. for example first value is 2800000.0 , i want this value to be filled 6 times.

amount      times       
2800000.0    6
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0   
4750000.0    4         
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0   
nan     0    0    

Desired output:

amount      times       
2800000.0    6
2800000.0    0   
2800000.0    0   
2800000.0    0   
2800000.0    0   
2800000.0    0   
2800000.0    0   
4750000.0    4         
4750000.0    0   
4750000.0    0   
4750000.0    0   
4750000.0    0   
nan     0    0   
nan     0    0   

Answer 1

First create groups by test non missing values with cumulative sum and pass to GroupBy.apply with lambda function with Series.ffill with limit by first value of times per groups:

#if necessary convert strings t onumeric and NaNs
#df['amount'] = pd.to_numeric(df['amount'], errors='coerce')

print (df['amount'].dtype)
float64

g = df['amount'].notna().cumsum()

f = lambda x: x['amount'].ffill(limit=x['times'].iat[0])
df['amount'] = df.groupby(g, group_keys=False).apply(f)
print (df)
       amount  times
0   2800000.0      6
1   2800000.0      0
2   2800000.0      0
3   2800000.0      0
4   2800000.0      0
5   2800000.0      0
6   2800000.0      0
7   4750000.0      4
8   4750000.0      0
9   4750000.0      0
10  4750000.0      0
11  4750000.0      0
12        NaN      0
13        NaN      0